Robust i-vector based adaptation of DNN acoustic model for speech recognition

Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

Volumn 2015-January, Issue , 2015, Pages 2877-2881

  Garimella, Sri ^a   Mandal, Arindam ^a   Strom, Nikko ^a   Hoffmeister, Bjorn ^a   Matsoukas, Spyros ^a   Parthasarathi, Sree Hari Krishnan ^a  

^a AMAZON   (United States)

Author keywords

Adaptation of DNN acoustic model; I vector; Robustness; Speech recognition

Indexed keywords

HIDDEN MARKOV MODELS; MARKOV PROCESSES; ROBUSTNESS (CONTROL SYSTEMS); SPEECH; SPEECH COMMUNICATION; VECTORS;

ACOUSTIC FEATURES; ACOUSTIC MODEL; AUTOMATIC SPEECH RECOGNITION; DEEP NEURAL NETWORKS; I VECTORS; SPEAKER INDEPENDENTS; UNIVERSAL BACKGROUND MODEL; WORD ERROR RATE;

SPEECH RECOGNITION;

EID: 84959142471     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. G. Hinton, L. Deng, D. Yu, G. E. Dahl, A.-r. Mohamed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, T. N. Sainath et al., "Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups, " IEEE Signal Processing Magazine, vol. 29, no. 6, pp. 82-97, 2012.
2. P. Swietojanski, A. Ghoshal, and S. Renals, "Revisiting hybrid and gmm-hmm system combination techniques, " in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.
3. S. H. K. Parthasarathi, B. Hoffmeister, S. Matsoukas, A. Mandal, N. Strom, and S. Garimella, "fmllr based feature-space speaker adaptation of dnn acoustic models. " in INTERSPEECH, 2015.
4. H. Liao, "Speaker adaptation of context dependent deep neural networks, " in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.
5. N. Strom, "Speaker adaptation by modeling the speaker variation in a continuous speech recognition system, " in Proceedings of Fourth International Conference on Spoken Language (ICSLP), 1996.
6. M. L. Seltzer, D. Yu, and Y. Wang, "An investigation of deep neural networks for noise robust speech recognition, " in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013.
7. G. Saon, H. Soltau, D. Nahamoo, and M. Picheny, "Speaker adaptation of neural network acoustic models using i-vectors, " in IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), 2013.
8. A. Senior and I. Lopez-Moreno, "Improving dnn speaker independence with i-vector inputs, " in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.
9. N. Dehak, P. Kenny, R. Dehak, P. Dumouchel, and P. Ouellet, "Front-end factor analysis for speaker verification, " IEEE Transactions on Audio, Speech, and Language Processing, vol. 19, no. 4, pp. 788-798, 2011.
10. P. Kenny, "Joint factor analysis of speaker and session variability: Theory and algorithms, " CRIM, Montreal, (Report) CRIM-06/08-13, 2005.
11. Y. Lei, N. Scheffer, L. Ferrer, and M. McLaren, "A novel scheme for speaker recognition using a phonetically-aware deep neural network, " in In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, 2014.
12. M. J. Gales, "Semi-tied covariance matrices for hidden markov models, " IEEE Transactions on Speech and Audio Processing, vol. 7, no. 3, pp. 272-281, 1999.